37 research outputs found
Search-Based Motion Planning for Performance Autonomous Driving
Driving on the limits of vehicle dynamics requires predictive planning of
future vehicle states. In this work, a search-based motion planning is used to
generate suitable reference trajectories of dynamic vehicle states with the
goal to achieve the minimum lap time on slippery roads. The search-based
approach enables to explicitly consider a nonlinear vehicle dynamics model as
well as constraints on states and inputs so that even challenging scenarios can
be achieved in a safe and optimal way. The algorithm performance is evaluated
in simulated driving on a track with segments of different curvatures.Comment: Accepted to IAVSD 201
Investigation of seat suspensions with embedded negative stiffness elements for isolating bus users’ whole-body vibrations
Bus drivers are a group at risk of often suffering from musculoskeletal problems, such as low-back pain, while bus passengers on the last-row seats experience accelerations of high values. In this paper, the contribution of K-seat in decreasing the above concern is investigated with a detailed simulation study. The K-seat model, a seat with a suspension that functions according to the KDamper concept, which combines a negative stiffness element with a passive one, is benchmarked against the conventional passive seat (PS) in terms of comfort when applied to different bus users’ seats. More specifically, it is tested in the driver’s and two different passengers’ seats, one from the rear overhang and one from the middle part. For the benchmark shake, both are optimized by applying excitations that correspond to real intercity bus floor responses when it drives over a real road profile. Then a human model is placed on the seats in order to compare their optimum solutions in terms of the user’s whole-body vibrations (WBVs), using objective comfort metrics. Based on the results, the K-seat improves significantly the comfort of the users (~92%) compared to the PS, while it achieves a similar decrease in the maximum values of the user’s back accelerations (~97%)
Feedback brake distribution control for minimum pitch
The distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as ‘ideal’ distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear brak- ing forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehi- cle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state esti- mation and implemented in a high fidelity environment together with the model predictive control strategy. The proposed solution is compared with the reference ‘ideal’ distribution as well as another previous feed-forward solution
Effect of handling characteristics on minimum time cornering with torque vectoring
In this paper, the effect of both passive and actively-modified vehicle handling characteristics
on minimum time manoeuvring for vehicles with 4-wheel torque vectoring (TV) capability
is studied. First, a baseline optimal torque vectoring strategy is sought, independent of any
causal control law. An optimal control problem (OCP) is initially formulated considering
4 independent wheel torque inputs, together with the steering angle rate, as the control
variables. Using this formulation, the performance benefit using torque vectoring against
an electric drive train with a fixed torque distribution, is demonstrated. The sensitivity
of TV-controlled manoeuvre time to the passive understeer gradient of the vehicle is
then studied. A second formulation of the optimal control problem is introduced where a
closed-loop torque vectoring controller is incorporated into the system dynamics of the OCP.
This formulation allows the effect of actively modifying a vehicle’s handling characteristic
via TV on its minimum time cornering performance of the vehicle to be assessed. In
particular, the effect of the target understeer gradient as the key tuning parameter of the
literature-standard steady-state linear single-track model yaw rate reference is analysed
Evaluation of optimal yaw rate reference for electric vehicle torque vectoring
This work evaluates the intrinsic contribution of the yaw rate reference to the overall handling performance of an electric vehicle with torque vectoring control - in terms of minimum-time manoeuvring. A range of yaw rate references are compared through optimal control simulations incorporating closed-loop controller dynamics. Results show yaw rate reference has a significant effect on manoeuvre time
On the optimality of handbrake cornering
The aim of this paper is to investigate the optimality of the handbrake cornering technique for a Front Wheel Drive vehicle. Nonlinear Optimal Control theory is used to formulate the problem of optimal cornering and to simulate manoeuvres used by race drivers. Handbrake cornering is optimal with an appropriate selection of the minimization cost. The optimal solution is validated against data collected during the execution of the technique by an expert race driver on a loose off-road surface. Further optimization results considering high adhesion road surface are obtained to show that the optimality of the technique is not affected by the road conditions
EXTENSION OF THE LUGRE DYNAMIC TIRE FRICTION MODEL TO 2D MOTION
An extension of the LuGre dynamic friction model from longitudinal motion to longitudinal/lateral motion is developed. Applying this model to the motion of a tire we derive a model for tire-road contact forces and moments. A comparison of the steadystate behaviour of the dynamic model with existing static tire friction models is also presented. This comparison allows one to determine the values of the parameters for the new model. Introducing a set of mean states we reduce the order of the system and derive a model in lumped form which is useful for control purposes.